Title : 
Upper bounds for robustness of CNN templates and a design approach for robust templates
         
        
            Author : 
Mirzai, Bahram ; Moschytz, George S.
         
        
            Author_Institution : 
Signal & Inf. Process. Lab., Swiss Federal Inst. of Technol., Zurich, Switzerland
         
        
        
        
        
        
            Abstract : 
CNNs constitute a class of spatially discrete, nonlinear dynamic systems. Once the inputs and the states are initialized, the dynamic of a CNN is determined by a set of parameters, so-called templates. We investigate issues concerning the dynamic behavior of a CNN due to variations in template values. In particular, we derive, based on the output invariance at the equilibrium, upper bounds for these variations. Furthermore, a general design approach for robust templates is proposed
         
        
            Keywords : 
cellular neural nets; discrete systems; nonlinear dynamical systems; robust control; CNN template; design; output invariance; robustness; spatially discrete nonlinear dynamic system; upper bound; Cellular neural networks; Differential equations; Information processing; Laboratories; Neural networks; Neurofeedback; Robustness; Signal processing; Upper bound; Very large scale integration;
         
        
        
        
            Conference_Titel : 
Circuits and Systems, 1996. ISCAS '96., Connecting the World., 1996 IEEE International Symposium on
         
        
            Conference_Location : 
Atlanta, GA
         
        
            Print_ISBN : 
0-7803-3073-0
         
        
        
            DOI : 
10.1109/ISCAS.1996.541589